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A New Solution to Time Series Inference in Spurious Regression Problems

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  • Hrishikesh D. Vinod

    (Fordham University, Department of Economics)

Abstract

Phillips (1986) provides asymptotic theory for regressions that relate nonstationary time series including those integrated of order 1, I(1). A practical implication of the literature on spurious regression is that one cannot trust the usual confidence intervals. In the absence of prior knowledge that two series are cointegrated, it is therefore recommended that after carrying out unit root tests we work with differenced or detrended series instead of original data in levels. We propose a new alternative for obtaining confidence intervals based on the Maximum Entropy bootstrap explained in Vinod and Lopez-de-Lacalle (2009). An extensive Monte Carlo simulation shows that our proposal can provide more reliable conservative confidence intervals than traditional, differencing and block bootstrap (BB) intervals.

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Bibliographic Info

Paper provided by Fordham University, Department of Economics in its series Fordham Economics Discussion Paper Series with number dp2010-01.

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Date of creation: 2010
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Handle: RePEc:frd:wpaper:dp2010-01

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Web page: http://www.fordham.edu/economics/
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Keywords: Bootstrap; simulation; confidence intervals;

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Cited by:
  1. A. Talha Yalta, 2011. "Analyzing Energy Consumption and GDP Nexus Using Maximum Entropy Bootstrap: The Case of Turkey," Working Papers 1103, TOBB University of Economics and Technology, Department of Economics.
  2. Fong, Wai Mun, 2013. "Footprints in the market: Hedge funds and the carry trade," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 41-59.

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